Even after a tumor has been surgically removed or shrunk with drugs, a few remaining aggressive cancer cells can instigate the growth and spread of new tumors.
“These cancer stem cells behave differently from other cells and therefore have a significant impact on cancer recurrence”, said Miao-Ping Chien, PhD, an assistant professor at the Erasmus University Medical Center, in the Netherlands.
Chien and her partner Daan Brinks, PhD, an investigator at the department of imaging physics at Delft University in the Netherlands collaborated to develop a new method to detect these villainous cells.
“Tumor heterogeneity is the leading cause of therapy resistance, recurrence and metastasis. Our interdisciplinary training suggested a solution to this heterogeneity problem: identifying the cells that show aggressive behavior, isolating them, and sequencing them to understand the underlying molecular causes of said behavior,” said Chien.
The researchers have developed a functional single-cell selection pipeline (fSCS) that selects groups of cancer cells based on attributes such as spindle morphology, migration speed or cell division, while maintaining cell viability, and labels these cells in a heterogenous pool of cancer cells. Using a method called FUNseq (functional single-cell sequencing) the researchers then sequence the labeled single cells and correlate the genetic data with their functional features.
The study was published on March 17, 2022, in the journal Nature Biomedical Engineering, in an article titled “Linking the genotypes and phenotypes of cancer cells in heterogenous populations via real-time optical tagging and image analysis.” The new method, will make it possible to detect aggressive cancer cells, label them with optical tags, separate them from the other cells and determine their RNA sequence, to develop cancer drugs and biomarkers in less time than existing technology allows.
Chien said, “We’ve known that they’re there for a long time, but the Holy Grail is to be able to sequence precisely those cells, to find out their DNA and RNA content. Merely examining the outside of the cell is not enough for these special cells. Although certain characteristic substances can be found there, the so-called biomarkers, these are quite changeable in such an aggressive cell.” Complementing genetic characteristics of these cells with their phenotypes is therefore critical to understand how these cells work, and how they can be targeted using precise drugs.
The functional hallmarks of aggressive cancer cells are rapid migration and division into three or four daughter cells unlike normal cells that move far less and always split into two cells.
The two teams developed an ultrawide-field microscope that images a large number of cells simultaneously and a software that quickly analyzes streams of these images to identify cells behaving aggressively before they escape, among tens of thousands of cells.
“We developed a completely new pipeline for the identification, tracking, isolation and sequencing of cells with aggressive behaviors. Novel elements included a new type of homebuilt microscope, real time cell identification and tracking algorithms and a new photochemical process to “tag” cells of interest,” said Chien.
The microscope directs a patterned light beam onto the detected aggressive cancer cells that light up because the cancer tissue was pretreated with light-activated proteins or dyes. The lit-up cells are then selected, and their RNA is sequenced and analyzed.
“We can now determine the genetic profile of the aggressive cancer cells. This was not so easy to do at first, because you have to deal with all the challenges of imaging, selecting and determining the RNA sequence in one go,” said Chien. “We’ve succeeded in discovering a mechanism within a few months, whereas others needed quite a few years with the existing techniques. Maybe, with our method, it can eventually be done within a few weeks.”
Applying their new platform, the team identified TGFβ and NF-κB as pathways that cause rapid migration and loosely organized, mesenchymal-like morphology. The platform also indicated different genes and pathways that are excessively expressed in different cancer cell lines.
“Once we know the underlying molecular causes of this behavior, this information can be used to develop biomarkers to predict disease progression or treatment response; or drugs that tackle metastasis or therapy resistance,” Chien added.
Chien and Brinks are starting a company called UFO Biosciences where researchers from around the world can send in samples for analysis.
“We are very interested in using the developed pipeline to gain a more detailed understanding of the underlying mechanisms of, for instance, therapy resistance in aggressive cancers like glioblastoma,” said Chien. “On the technical side, we hope to expand the types of behavior we can detect, curate a database of linked genotype-phenotype data and use this for the development of biomarkers and druggable targets.”